Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics
- Author
- Carolin Grones, Thomas Eekhout (UGent) , Dongbo Shi, Manuel Neumann, Lea S. Berg, Yuji Ke (UGent) , Rachel Shahan, Kevin L. Cox Jr, Fabio Gomez-Cano, Hilde Nelissen (UGent) , Jan U. Lohmann, Stefania Giacomello, Olivier C. Martin, Benjamin Cole, Jia-Wei Wang, Kerstin Kaufmann, Michael T. Raissig, Gergo Palfalvi, Thomas Greb, Marc Libault and Bert De Rybel (UGent)
- Organization
- Project
- Abstract
- Single-cell and single-nucleus RNA-sequencing (scRNA-seq and snRNA-seq) technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality datasets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation, and to make the data readily available to the community in this fast-developing field of research.
- Keywords
- Cell Biology, Plant Science, GENE-EXPRESSION, SPATIAL TRANSCRIPTOMICS, ROOT, TISSUE, CELLS, MAIZE, RESOLUTION, MAP, MECHANISMS, CIRCUITRY
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HMDTA2Q5FK6ATG8AHBSD75AP
- MLA
- Grones, Carolin, et al. “Best Practices for the Execution, Analysis, and Data Storage of Plant Single-Cell/Nucleus Transcriptomics.” PLANT CELL, vol. 36, no. 4, 2024, pp. 812–28, doi:10.1093/plcell/koae003.
- APA
- Grones, C., Eekhout, T., Shi, D., Neumann, M., Berg, L. S., Ke, Y., … De Rybel, B. (2024). Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics. https://doi.org/10.1093/plcell/koae003
- Chicago author-date
- Grones, Carolin, Thomas Eekhout, Dongbo Shi, Manuel Neumann, Lea S. Berg, Yuji Ke, Rachel Shahan, et al. 2024. “Best Practices for the Execution, Analysis, and Data Storage of Plant Single-Cell/Nucleus Transcriptomics.” PLANT CELL. https://doi.org/10.1093/plcell/koae003.
- Chicago author-date (all authors)
- Grones, Carolin, Thomas Eekhout, Dongbo Shi, Manuel Neumann, Lea S. Berg, Yuji Ke, Rachel Shahan, Kevin L. Cox Jr, Fabio Gomez-Cano, Hilde Nelissen, Jan U. Lohmann, Stefania Giacomello, Olivier C. Martin, Benjamin Cole, Jia-Wei Wang, Kerstin Kaufmann, Michael T. Raissig, Gergo Palfalvi, Thomas Greb, Marc Libault, and Bert De Rybel. 2024. “Best Practices for the Execution, Analysis, and Data Storage of Plant Single-Cell/Nucleus Transcriptomics.” PLANT CELL. doi:10.1093/plcell/koae003.
- Vancouver
- 1.Grones C, Eekhout T, Shi D, Neumann M, Berg LS, Ke Y, et al. Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics. Vol. 36, PLANT CELL. 2024. p. 812–28.
- IEEE
- [1]C. Grones et al., “Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics,” PLANT CELL, vol. 36, no. 4. pp. 812–828, 2024.
@misc{01HMDTA2Q5FK6ATG8AHBSD75AP,
abstract = {{Single-cell and single-nucleus RNA-sequencing (scRNA-seq and snRNA-seq) technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality datasets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation, and to make the data readily available to the community in this fast-developing field of research.}},
author = {{Grones, Carolin and Eekhout, Thomas and Shi, Dongbo and Neumann, Manuel and Berg, Lea S. and Ke, Yuji and Shahan, Rachel and Cox Jr, Kevin L. and Gomez-Cano, Fabio and Nelissen, Hilde and Lohmann, Jan U. and Giacomello, Stefania and Martin, Olivier C. and Cole, Benjamin and Wang, Jia-Wei and Kaufmann, Kerstin and Raissig, Michael T. and Palfalvi, Gergo and Greb, Thomas and Libault, Marc and De Rybel, Bert}},
issn = {{1040-4651}},
keywords = {{Cell Biology,Plant Science,GENE-EXPRESSION,SPATIAL TRANSCRIPTOMICS,ROOT,TISSUE,CELLS,MAIZE,RESOLUTION,MAP,MECHANISMS,CIRCUITRY}},
language = {{eng}},
number = {{4}},
pages = {{812--828}},
series = {{PLANT CELL}},
title = {{Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics}},
url = {{http://doi.org/10.1093/plcell/koae003}},
volume = {{36}},
year = {{2024}},
}
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